Coping with neck and low back pain in the general population.
Bibliographic record
Abstract
This study had 2 objectives: (a) to assess the psychometric properties of the Pain Management Inventory (PMI; G. K. Brown & P. M. Nicassio, 1987) with individuals in the general population with neck or low back pain, and (b) to assess the relationship between pain severity and coping. Data were taken from a mailed survey of a random sample of adults residing in Saskatchewan, Canada. Results validated the 2-factor structure of the PMI and provided evidence for the internal consistency of the coping subscales. Regression analyses revealed that passive coping was associated with being married, greater pain severity, depression, and poor health. Active coping was associated with female gender, higher education, less depression, good health, and frequent exercise. This study provides psychometric data to support the use of the PMI and information about factors associated with use of active and passive coping strategies in pain sufferers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".